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Advanced Climate Simulation and Observation

Advanced Climate Simulation and Observation

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Global climate changes, particularly extreme events, affect terrestrial carbon, water, and energy exchanges between the atmosphere, biosphere, and lithosphere, thus controlling freshwater availability, floods, and droughts. Therefore, it is urgent and necessary to develop advanced climate simulation and observation approaches and models related to extreme climate events. Advanced climate simulation and observation can improve the accurate prediction of climate change and long-term trends, which can mitigate climate events' impacts on human society. Under these conditions, this reprint aims to introduce advanced climate simulation and observation approaches to various practical studies related to climate variations, including the global climate models (GCMs) and regional climate models (RCMs), mitigation studies of high-impact climate events, predictions of climate variations, and some new artificial intelligence. Twenty-two papers have been collected in this reprint, with eight original research articles reporting on climate change and six papers reporting on climate change's impact on society and the economy. Meanwhile, three papers reported climate change's impact on agriculture, and climate change's impact on human health was studied in five articles.

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Keywords

  • 10 m wind speed
  • accumulated temperature
  • agricultural air pollution
  • air pollutants
  • Air Pollution
  • air quality satisfaction
  • apparent temperature
  • AQI
  • arid climate
  • ARIMA model
  • assessment of economic losses
  • binomial logistic regression
  • burst words
  • carbon emission performance
  • China
  • CiteSpace
  • Climate Change
  • climate variables
  • CMIP6
  • co-occurrence keywords
  • collective effect
  • cropland
  • cumulative risk
  • cumulus parameterization schemes
  • decoupling index
  • drought
  • Earth sciences
  • Ecological Niche Model
  • economic loss prediction
  • economy of scale
  • elevated [CO2]
  • environmental Kuznets curve
  • Environmental regulation
  • environmental variables
  • experienced utility
  • exposure
  • flooding
  • generalized additive model
  • generative adversarial network (GAN)
  • geographically weighted regression
  • Geothermal Energy
  • green innovation efficiency
  • greenhouse
  • gridded datasets
  • haze
  • haze pollution
  • HDI
  • health utility value
  • heat exchanger
  • heat map
  • heavy precipitation
  • hydrological modeling
  • IAP-AGCM
  • income effect
  • input-output model
  • interannual variation
  • Issyk-Kul
  • labor migration
  • leaf nitrogen monitoring
  • LMDI
  • Machine learning
  • Mainland China
  • mediation effect
  • meteorological factors
  • Meteorology & climatology
  • model evaluation
  • mountain-type zoonotic visceral leishmaniasis
  • n/a
  • neural network model
  • nitrogen management
  • panel spatial error model
  • parameterization scheme
  • penalized distributed lag non-linear model
  • Pulmonary Tuberculosis
  • Quality of life
  • rainfall simulation
  • Reference, information & interdisciplinary subjects
  • RegCM4.5
  • regional climate model
  • Research & information: general
  • respiratory and cardiovascular diseases
  • respiratory disease
  • SBM of super-efficiency
  • scale effect
  • scenario analysis
  • scPDSI
  • sensitivity analysis
  • sensitivity of physical processes
  • snowmelt
  • SPAD
  • spatial heterogeneity
  • special spillover effect
  • sustained exposure to pollution
  • SWAT
  • system GMM estimation
  • Temporal and Spatial GAN (TSGAN)
  • Thailand
  • thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
  • transmission risk prediction
  • underground temperature
  • Upper Vakhsh River Basin
  • urban population agglomeration
  • Visual analysis
  • warming
  • Water balance
  • weather radar nowcasting
  • western Tianshan Mountains
  • WRF
  • yield per unit area of beans

Links

DOI: 10.3390/books978-3-0365-9139-1

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